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基于线阵有限视角的光声断层成像重建研究。

Investigation of photoacoustic tomography reconstruction with a limited view from linear array.

机构信息

University of British Columbia, Department of Electrical and Computer Engineering, Vancouver, Canada.

University of British Columbia, Department of Mechanical Engineering, Vancouver, Canada.

出版信息

J Biomed Opt. 2021 Sep;26(9). doi: 10.1117/1.JBO.26.9.096009.

Abstract

SIGNIFICANCE

As linear array transducers are widely used in clinical ultrasound imaging, photoacoustic tomography (PAT) with linear arrays is similarly suitable for clinical applications. However, due to the limited-view problem, a linear array has limited performance and leads to artifacts and blurring, which has hindered its broader application. There is a need to address the limited-view problem in PAT imaging with linear arrays.

AIM

We investigate potential approaches for improving PAT reconstruction from linear array, by optimizing the detection geometry and implementing iterative reconstruction.

APPROACH

PAT imaging with a single-array, dual-probe configurations in parallel-shape and L-shape, and square-shape configuration are compared in simulations and phantom experiments. An iterative model-based algorithm based on the variance-reduced stochastic gradient descent (VR-SGD) method is implemented. The optimum configuration found in simulation is validated on phantom experiments.

RESULTS

PAT imaging with dual-probe detection and VR-SGD algorithm is found to improve the limited-view problem compared to a single probe and provide comparable performance as full-view geometry in simulation. This configuration is validated in experiments where more complete structure is obtained with reduced artifacts compared with a single array.

CONCLUSIONS

PAT with dual-probe detection and iterative reconstruction is a promising solution to the limited-view problem of linear arrays.

摘要

意义

由于线性阵列换能器在临床超声成像中得到了广泛应用,因此线性阵列的光声断层扫描(PAT)同样适用于临床应用。然而,由于视场有限的问题,线性阵列的性能有限,导致伪影和模糊,这阻碍了其更广泛的应用。需要解决线性阵列 PAT 成像中的视场有限问题。

目的

我们通过优化检测几何形状和实施迭代重建,研究了从线性阵列改善 PAT 重建的潜在方法。

方法

在模拟和体模实验中比较了具有平行形状和 L 形状以及正方形形状配置的单个阵列、双探头配置的 PAT 成像。实现了基于方差减少随机梯度下降(VR-SGD)方法的迭代模型算法。在体模实验中验证了模拟中找到的最佳配置。

结果

与单个探头相比,双探头检测和 VR-SGD 算法的 PAT 成像发现可以改善视场有限的问题,并在模拟中提供与全视场几何形状相当的性能。该配置在实验中得到了验证,与单个阵列相比,它获得了更完整的结构,并且伪影减少。

结论

具有双探头检测和迭代重建的 PAT 是解决线性阵列视场有限问题的一种有前途的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1366/8477256/581c5b2d33b4/JBO-026-096009-g001.jpg

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